Comparer des méthodes

	Méthodes mixtes d'intervention à poids égal	Conception multiphasique à méthodes mixtes
Domaine	Conception de la recherche	Conception de la recherche
Famille	Process / pipeline	Process / pipeline
Année d'origine	2000s–2010s	2007 (first edition of Designing and Conducting Mixed Methods Research)
Auteur d'origine	Creswell & Plano Clark (weighting framework); intervention design tradition in mixed methods	John W. Creswell & Vicki L. Plano Clark
Type	Mixed methods research design	Mixed methods research design
Source fondatrice	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). SAGE Publications. ISBN: 978-1483344379	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483substitute
Alias	equal-priority intervention MMR, balanced intervention mixed methods, QUAL=QUAN intervention design, equal-status intervention mixed design	multiphase design, multiproject mixed methods, programmatic mixed methods, multistage mixed methods
Apparentées	6	6
Résumé	Equal-weight intervention mixed methods is a research design in which both quantitative and qualitative strands are assigned equal priority and are embedded within or alongside an intervention, program, or experiment. The design evaluates not only whether an intervention works (QUAN outcomes) but also how and why it works or fails (QUAL processes), with neither strand treated as secondary. It is particularly suited to program evaluation, clinical trials with process components, and educational or social interventions.	The multiphase mixed methods design is a sustained research program in which quantitative and qualitative strands are combined across three or more sequential phases — or across multiple related projects — to address a central program objective. Each phase builds on the prior phase's findings, making the design well-suited to long-term evaluation, intervention development, and large-scale program assessment where a single data-collection cycle cannot fully address the complexity of the research problem.